Abstract
The Ripple Down Rule (RDR) is a knowledge acquisition scheme which has been successfully used in large scale commercial applications. Most notable is the use of the scheme in building a knowledge base for interpreting pathology results. Unlike machine learning algorithms which construct theories for raw data, the commercial system using the RDR scheme requires some interaction with an expert to correct erroneous interpretations. However, the frequency of such interactions is very low. Furthermore, the simplicity of the interaction means that a knowledge engineer is not required when updating a knowledge base. A number of RDR variants have been devised for different applications. While Scheffer has given operational semantics to one variant of RDR, translations of RDR into classical logics has not yet been presented in the literature. This paper will show how two variants of RDR, single classification RDR (SCRDR) and multiple classification RDR (MCRDR), have a propositional or first-order core tied with case specific defaults. Such a translation will be used to highlight properties of the RDR scheme which make it successful. Similarities and differences in the two variants will be discussed and RDR revision will also be analysed.
This is an extension of a paper presented at the Fourth Australian Knowledge Acquisition Workshop, 1999, Sydney Australia.
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Kwok, R.B. (2000). Translations of Ripple Down Rules into Logic Formalisms. In: Dieng, R., Corby, O. (eds) Knowledge Engineering and Knowledge Management Methods, Models, and Tools. EKAW 2000. Lecture Notes in Computer Science(), vol 1937. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39967-4_28
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DOI: https://doi.org/10.1007/3-540-39967-4_28
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